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Measurement of hydrophobicity distribution in proteins – complete redundant Protein Data Bank

100%

Sałapa K. , Kalinowska B. , Jadczyk T. , Roterman I.

tom Vol. 8, no. 2

195--206

The divergence entropy: O/T and O/R measuring the distance between observed/theoretical and observed/random distributions was applied to identify the category of protein structures in respect to the hydrophobic core in protein molecules. The naive interpretation was applied treating the proteins of O/T < O/R as the molecules of hydrophobic core accordant with the theoretically assumed. The proteins of O/T > O/R are treated as representing the hydrophobic core not accordant with the assumed one. The large scale computing was performed (PDB data set) to reveal whether other than simple inequality relation should be used for this identification. The cluster analysis was applied to identify the relation O/T versus O/R as the discrimination factor to classify the category of proteins in respect to their structural form of hydrophobic core.

The variability of protein structure with respect to the hydrophobic core

100%

Banach M. , Wiśniowski Z. , Kalinowska B. , Konieczny L. , Roterman I.

Bio-Algorithms and Med-Systems

2017

tom Vol. 13, no. 2

63--67

The application of the fuzzy oil drop model to the analysis of protein structure is shown using two proteins. The selection of these two examples is due to their opposite character. Two proteins were selected representing very high order and very high disorder with respect to the organized uni-central hydrophobic core in proteins (one centrally localized concentration of high hydrophobicity). These two cases are to show examples of the large spectrum of variability of local organization of the hydrophobic core in proteins. The importance of the observation presented in this paper is significant with respect to large sets of proteins discussed in separate publications.

Protein intrachain contact prediction with most interacting residues (MIR)

88%

Acuña R. , Lacroix Z. , Papandreou N. , Chomilier J.

tom Vol. 10, no. 4

227--242

The transition state ensemble during the folding process of globular proteins occurs when a sufficient number of intrachain contacts are formed, mainly, but not exclusively, due to hydrophobic interactions. These contacts are related to the folding nucleus, and they contribute to the stability of the native structure, although they may disappear after the energetic barrier of transition states has been passed. A number of structure and sequence analyses, as well as protein engineering studies, have shown that the signature of the folding nucleus is surprisingly present in the native three-dimensional structure, in the form of closed loops, and also in the early folding events. These findings support the idea that the residues of the folding nucleus become buried in the very first folding events, therefore helping the formation of closed loops that act as anchor structures, speed up the process, and overcome the Levinthal paradox. We present here a review of an algorithm intended to simulate in a discrete space the early steps of the folding process. It is based on a Monte Carlo simulation where perturbations, or moves, are randomly applied to residues within a sequence. In contrast with many technically similar approaches, this model does not intend to fold the protein but to calculate the number of non-covalent neighbors of each residue, during the early steps of the folding process. Amino acids along the sequence are categorized as most interacting residues (MIRs) or least interacting residues. The MIR method can be applied under a variety of circumstances. In the cases tested thus far, MIR has successfully identified the exact residue whose mutation causes a switch in conformation. This follows with the idea that MIR identifies residues that are important in the folding process. Most MIR positions correspond to hydrophobic residues; correspondingly, MIRs have zero or very low accessible surface area. Alongside the review of the MIR method, we present a new postprocessing method called smoothed MIR (SMIR), which refines the original MIR method by exploiting the knowledge of residue hydrophobicity. We review known results and present new ones, focusing on the ability of MIR to predict structural changes, secondary structure, and the improved precision with the SMIR method.